Complex Network Topology On The Ofc Model Dynamic Behavior

A large number of complex systems in nature can be described by various kinds of networks, which concern the subjects of nature, physics, biology, society, economy, environment and ecology etc. Complex network is a new discipline exploring complex systems, which has gotten great attentions in recent years both at home and abroad. Any complex system can be abstracted as a network composed by interactive individuals, thus network is universal and exists in nature and society. Mathematicians and physicists often concerned about whether there is a edge between the nodes. They do not care for the location of the node, whether the edge is long or short, curved or straight, whether there is intersection or not and so on. Here, the network which is independent of the specific location of nodes and the concrete form of edges, and the corresponding structure is called the network topology. This paper studies self-organized criticality (SOC) on the complex network as well as the effects of complex network on the SOC.For the first time we have considered the effects of neural aging. The aging mechanism is introduced on the basis of small world neural network, and we have compared the network structure between random aging neural network and the original one. The avalanche dynamics and electroencephalograph (EEG)-like wave have been discussed based on neural network with or without aging mechanisms. We analyzed the complex behavior of EEG-like wave and found out that the simulation results were qualitatively corresponding to the actual behavior of neural aging. We found that if the brain worked at the SOC state it had the ability to relieve some effects caused by aging. The neural network structure between selective aging and random aging mechanisms has been compared, and the robustness of neural network has been discussed. We give the avalanche dynamic behaviors of different aging mechanisms.It is very interesting to construct weighted scale free network model and discuss the Olami-Feder-Christensen (OFC) model on weighted scale free topology. Based on the Yook-Jeong-Barabasi-Tu (YJBT) network, we have discussed the OFC model and found that the OFC model on weighted scale free networks could be a very good presentation of self-organized criticality. We have shown the relationships among the node activity of weighted scale free networks, self-organized criticality and avalanche dynamics. Also, we have investigated the impact of edge weight on self-organized criticality and finite size scale. For the first time, we have discussed the period of weighted OFC model, the curve of the simulation and the actual statistics have the same scale free distribution. By discussing the weighted OFC model, we find that the original lattice network is not necessary to generate SOC behavior, and we get more reasonable avalanche dimension.Based on the analysis of Barabasi-Albert (BA) network and Barrat, Barthelemy and Vespignani (BBV) network, we find that they have only taken into consideration the weight distributed among the newly added nodes and the existing ones. But actually the interactions not only take place between newly added nodes and the old nodes, they also exist among existing ones. In view of this, we propose an evolved model with mixed mechanism of topological growth and inner selection. We analyzed the topology and property of the mixed model and found the model could generate a broader distribution of power-law. We give a new regulator parameters and discuss the assor-tativity of our model, etc.. At the same time, it is a better model to reflect the actual situation of scientific collaboration network. We have studied the effect of the network topology on the dynamic behavior of the promotion of OFC based on the above model. We consider the effects of different parameters on self-organized criticality, average avalanche and avalanche exponent. Also, the comparison of transient time and equilibrium point has been given based on different parameters. The properties between original model and the promotion model have been compared.